In vitro effects of nonsteroidal anti-inflammatory drugs on cyclooxygenase activity in dogs
Bibliographic record
Abstract
OBJECTIVE: To establish an in vitro assay and determine the differential suppressive activity of non steroidal anti-inflammatory drugs (NSAID) on cyclooxygenase (COX)-1 and COX-2 isoenzymes in dogs. PROCEDURE: COX activity was evaluated in the presence and absence of 4 NSAID (meloxicam, tolfenamic acid, carprofen, and ketoprofen), using a canine monocyte/macrophage cell line that constitutively expresses COX-1, but can be induced to express COX-2 when incubated with lipopolysaccharide. Inhibition of prostaglandin E2 TPGE2) synthesis by each NSAID was measured by enzyme immunoassay and attributed to specific COX-1 or COX-2 activity through assessment of COX messenger RNA expression by use of northern blot analysis and reverse transcription-polymerase chain reaction (RT-PCR). The COX selectivity of each drug was evaluated from dose-response curves by calculating a ratio (COX-1:COX-2) of inhibitory concentration values on the basis of concentrations that reduced PGE2 by 50% in each COX model. RESULTS: Meloxicam and tolfenamic acid preferentially inhibited COX-2, with meloxicam inhibiting COX-2 activity 12 times more effectively than COX-1 activity. Carprofen was only 1.75 times more selective for COX-2 than for COX-1, and ketoprofen was slightly more selective for COX-1. CONCLUSIONS: COX-1 and COX-2 were differentially sensitive to inhibition in vitro by NSAID. Meloxicam and tolfenamic acid were selective for COX-2. Effects of carprofen and ketoprofen approached equipotency against both isoenzymes. Selective COX-2 inhibitors are a new class of drugs with anti-inflammatory effects similar to conventional NSAID but with fewer adverse effects. Development of these agents for veterinary use would be facilitated by the convenience of using a canine cell line as a model system to screen COX-1 and COX-2 inhibitor activities in vitro.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".